raj-nandu
Area of Interest - Deep Learning Languages Known - Python, Java, C, C++, PHP and JavaScript. Deep Learning Frameworks - Tensorflow and Keras.
Mumbai
Pinned Repositories
HNI-Customer-Identification-Using-Face-Recognition
Every bank has a set of HNI(High net worth individual) customers. It's difficult for the bank staff to distinguish these customers from general customers. This project uses face recognition technology to identify HNI customers present in the bank. Whenever an HNI customer is detected, a picture of the customer taken via CCTV(Laptop's webcam is used in the code as of now) camera and also a picture from the database is sent to the bank staff via a notification generated on an android application. The bank staff then compares both these images and has two choices 1) Attend the customer. 2) Reject the notification(Useful if at all any non HNI customer is recognized falsely as an HNI customer).
assignment3-dataset
Ayurvihar
Bank-Churn-Rate-Prediction
An artificial neural network has been developed that can predict which customers are likely to leave the bank based on their information such as credit card score, geography, age, tenure, bank balance and gender.
Breast-Cancer-Complete-AI-Model-And-Web-Application
Cancer detection using two models. CNN for image analysis and a simple Neural Network to predict result using report data
DSR
Food-Delivery-System
Hackit
Online-Examination
Online-Examination-System
raj-nandu's Repositories
raj-nandu/Food-Delivery-System
raj-nandu/assignment3-dataset
raj-nandu/Bank-Churn-Rate-Prediction
An artificial neural network has been developed that can predict which customers are likely to leave the bank based on their information such as credit card score, geography, age, tenure, bank balance and gender.
raj-nandu/Topic-Modelling-in-Movie-Reviews
raj-nandu/Hackit
raj-nandu/Breast-Cancer-Complete-AI-Model-And-Web-Application
Cancer detection using two models. CNN for image analysis and a simple Neural Network to predict result using report data
raj-nandu/HNI-Customer-Identification-Using-Face-Recognition
Every bank has a set of HNI(High net worth individual) customers. It's difficult for the bank staff to distinguish these customers from general customers. This project uses face recognition technology to identify HNI customers present in the bank. Whenever an HNI customer is detected, a picture of the customer taken via CCTV(Laptop's webcam is used in the code as of now) camera and also a picture from the database is sent to the bank staff via a notification generated on an android application. The bank staff then compares both these images and has two choices 1) Attend the customer. 2) Reject the notification(Useful if at all any non HNI customer is recognized falsely as an HNI customer).
raj-nandu/DSR
raj-nandu/Online-Examination
raj-nandu/Online-Examination-System
raj-nandu/Ayurvihar